NRF 2026: How Retailers Are Taking the Next Step in the Transition to Agentic AI

Testing and Trust: The Next Hurdles

As retailers explore agentic AI, one theme comes up repeatedly: Testing is non-negotiable. Before autonomous systems can be trusted to make the right decisions consistently, organizations must validate them thoroughly. Only then can they hand off specific tasks with confidence.

“It’s a lot of education and proofs of concept to get there,” said Stevens. Testing helps build trust not just in the technology but across the organization.

That trust, however, intersects with another major challenge: change management. Retail processes are often deeply ingrained, and introducing tools that shift decision-making — or automate parts of it — can be disruptive. “Change management is hard,” Stevens said. “That’s the hardest part of any major transformation.”

Karen Beebe, CTO of the Bealls retail chain, said her team is staying focused on value. “We’re focusing on using AI for the most impactful things. We want to use it to help us make decisions quickly so we can move fast.”

For Stevens, the move toward agentic AI represents more than a technological shift. “It really is a cultural shift for the entire organization,” he said. “We’re trying to change the culture of the business, and we need to get business users involved.” At Groupe Dynamite, that includes using AI not just in IT but across creative and operational functions, including design and marketing.

READ MORE: How AI agents, data governance and workforce shifts are redefining retail in 2026.

Agentic AI in Day-to-Day Operations

Even before achieving fully agentic workflows, retailers are finding meaningful gains in everyday tasks. “We’re using AI a lot in day-to-day operations,” Stevens said, pointing to email drafting, presentations and content creation using Google AI tools. “I’m surprised how much the business has embraced it.”

Rather than a threat to jobs, Stevens sees AI as a tool for handling complexity. “There’s been a lot of talk about AI taking people’s jobs, but it’s not that,” he explained. “It’s the complex tasks that AI can help us do. AI can help us accomplish complex tasks really quickly.”

For most retailers, the immediate goal is clear: Free up employee time and reduce operational friction. As Stevens put it, his company is prioritizing use cases that can “save time and money” while improving speed and accuracy.

Andy Szanger, director of strategic industries at CDW, noted that retailers are increasingly past the experimentation phase. “AI in retail has really moved beyond the pilots,” he said. “The question for many retailers is, how do they scale it?”

Finding the Right Use Cases

At Boot Barn, the first step was simple: Identify where AI could create immediate, measurable impact. “The first thing we wanted to see was what use cases applied to Boot Barn,” said Federico Gelso, the retailer’s director of IT. One successful effort focused on closing the knowledge gap between experienced and new store associates.

Boot Barn deployed a chatbot that gives newer employees fast access to product information, policies and procedures — enabling them to serve customers confidently without relying on veteran employees who may be tied up with other tasks. This democratized access to knowledge, Gelso said, and helped create a more consistent customer experience across the chain.

The company is now exploring AI for forecasting, planning, allocation, merchandising, logistics and customer analytics. “There are an infinite number of possibilities,” Gelso said.

Other retailers are similarly discovering both customer-facing and operational use cases. From demand forecasting to store-level decision support, the range of potential applications continues to expand.

Rewriting the Customer Journey

Agentic AI also stands to reshape how consumers shop online. Stevens expects AI-enabled search to significantly change behavior. Instead of scrolling through hundreds of products, shoppers can ask an AI agent to find exactly what they want — saving time and reducing friction.

However, this evolution raises new questions for retailers. Some worry that hyper-efficient AI search could strip away the enjoyment many shoppers find in browsing and discovering products organically. As with many aspects of agentic AI, retailers will need to find the right balance between speed, personalization and the experiential elements of shopping.

Start Small, Move Fast

With so many opportunities, experts say, the most important step is simply to begin. “We all know we’ve got to get moving, even if it’s just a small pilot,” said Eduardo Frias, field CTO for lifestyle at Shopify. “Pick a use case that works for your business and get going.”

Retailers that start experimenting now will be better positioned to identify where agentic AI can drive the biggest impact — and to put the right guardrails in place before scaling.

To learn more about NRF 2026, visit our conference page.